An Experimental Method for Studying Complex Choices

Gurney, Nikolos; King, Tyler; Miller, John H.

doi:10.1007/978-3-031-19679-9_6

Cited by 1 publication

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We adapted a rugged-landscape search metaphor, that was first introduced in biology to describe evolutionary selection (Wright 1932), in an interactive, complex choice task (Gurney, King, and Miller 2022). The fundamental idea of this metaphor is that evolutionary pressure, over many generations, guides organisms in a search for an optimal genotype across a genetic landscape where elevation on the landscape represents the fitness of a genotype.…”

Section: Experimental Paradigmmentioning

confidence: 99%

The Role of Heuristics and Biases During Complex Choices with an AI Teammate

Gurney¹,

Miller²,

Pynadath³

2023

Preprint

View full text Add to dashboard Cite

Behavioral scientists have classically documented aversion to algorithmic decision aids, from simple linear models to AI. Sentiment, however, is changing and possibly accelerating AI helper usage. AI assistance is, arguably, most valuable when humans must make complex choices. We argue that classic experimental methods used to study heuristics and biases are insufficient for studying complex choices made with AI helpers. We adapted an experimental paradigm designed for studying complex choices in such contexts. We show that framing and anchoring effects impact how people work with an AI helper and are predictive of choice outcomes. The evidence suggests that some participants, particularly those in a loss frame, put too much faith in the AI helper and experienced worse choice outcomes by doing so. The paradigm also generates computational modeling-friendly data allowing future studies of human-AI decision making.

show abstract

Section: Experimental Paradigmmentioning

confidence: 99%